NL
ENT-00001852 · Benchmark

NetHack Learning Environment

NetHack Learning Environment is a AI benchmark associated with Meta AI, classified in LXKeys.world as AI Benchmark / Evaluation.

Niveau IV ConnectéActifDocumenté
Fiche publique

Vue d’ensemble

NetHack Learning Environment is a documented AI dataset or benchmark associated with Meta AI. The record identifies its role in evaluation, training, measurement or comparison of intelligent systems, with emphasis on the source context and the type of capability it helps assess.

Chronologie

  1. 2020Initial benchmark release

    NetHack Learning Environment entered the documented public record in 2020. This event is retained at the precision supported by the Entry’s reviewed source history.

Capacités

Reinforcement learningEmbodied evaluationResearch reference

Limites connues

Benchmark scores depend on the exact dataset version, prompt or evaluation protocol, scoring implementation and contamination controls.Leaderboard performance should not be treated as a complete measure of real-world capability or safety.Benchmark relevance can decline as models, data and evaluation practices evolve.
Détail technique et structuré

Description technique

Structured LXKeys.world registry record for NetHack Learning Environment. Entity type: Benchmark; classification: AI Benchmark / Evaluation; creator/organization context: Facebook AI Research. Canonical source anchor: https://github.com/facebookresearch/nle. The record tracks source authority, first public appearance, timeline, capabilities, limitations, registry status and graph relationships. Automatic refresh is limited to sources explicitly classified as OFFICIAL and enabled for updates; documentary and research references remain non-authoritative unless reviewed.

Tags contrôlés

RoboticsBenchmarkAgentic Systems
Graphe relationnel

NetHack Learning Environment

Ouvrir dans le graphe complet
NetHack Learning Environment
Publié parSortante
Meta AI

NetHack Learning Environment is associated with Meta AI through its documented source context.

Couche lisible par machine

Données structurées de l’entrée pour les outils humains, les systèmes IA et les clients machine.

{
    "@context": [
        "https://schema.org",
        {
            "lxw": "https://lxkeys.world/schema/"
        }
    ],
    "@type": "Thing",
    "identifier": "ENT-00001852",
    "name": "NetHack Learning Environment",
    "alternateName": [],
    "additionalType": {
        "category": "Data and Evaluation",
        "type": "Benchmark",
        "subtype": "",
        "lxkeysEntity": false
    },
    "description": "NetHack Learning Environment is a AI benchmark associated with Meta AI, classified in LXKeys.world as AI Benchmark / Evaluation.",
    "creator": "Facebook AI Research",
    "url": "https://lxkeys.world/entry.php?id=ENT-00001852&lang=fr",
    "sameAs": "https://github.com/facebookresearch/nle",
    "image": "",
    "lxkeysWorld": {
        "worldId": "ENT-00001852",
        "kind": "Data and Evaluation",
        "type": "Benchmark",
        "subtype": "",
        "classification": "AI Benchmark / Evaluation",
        "organization": "Meta AI",
        "originContext": "Public AI and technical record",
        "firstPublicAppearance": "2020",
        "currentStatus": "Active",
        "documentationStatus": "Documented",
        "documentationIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
            "level": "Level IV Connected"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:29+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:29+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
        "facts": [],
        "capabilities": [
            "Reinforcement learning",
            "Embodied evaluation",
            "Research reference"
        ],
        "limitations": [
            "Benchmark scores depend on the exact dataset version, prompt or evaluation protocol, scoring implementation and contamination controls.",
            "Leaderboard performance should not be treated as a complete measure of real-world capability or safety.",
            "Benchmark relevance can decline as models, data and evaluation practices evolve."
        ],
        "tags": [
            "Robotics",
            "Benchmark",
            "Agentic Systems"
        ],
        "timeline": [
            {
                "date": "2020",
                "title": "Initial benchmark release",
                "description": "NetHack Learning Environment entered the documented public record in 2020. This event is retained at the precision supported by the Entry’s reviewed source history.",
                "source_url": "https://github.com/facebookresearch/nle",
                "verification_status": "source_backed_curated_baseline"
            }
        ],
        "relationships": [
            {
                "target": "Meta AI",
                "type": "Published by",
                "description": "NetHack Learning Environment is associated with Meta AI through its documented source context.",
                "evidence_level": "documentary",
                "target_id": "ENT-00000033"
            }
        ],
        "sources": [
            {
                "label": "Official project page or repository",
                "url": "https://github.com/facebookresearch/nle",
                "source_type": "Official Repository",
                "verification_status": "verified",
                "authority": "TRUSTED_PRIMARY",
                "role": "code_repository",
                "update_enabled": false,
                "authority_basis": "curated-corpus-refresh-2026-09-08"
            }
        ],
        "canonical": [],
        "imageMeta": []
    }
}
Preuves

Contribuer à cette entrée

Soumettez une source, une correction ou un commentaire. Les modifications publiques restent modérées.

Soumettre une preuve ou un commentaire

Commentaires approuvés

Aucun commentaire public approuvé pour le moment.